Customer Service Root Cause Analysis Report
Evaluating root cause analysis
Root Cause Analysis Reports, like other 'deliverables' can vary in quality. Each stakeholder can have their own qualitative and quantitative acceptance criteria. There are some general possibilities for evaluating root cause analysis outputs.
First: Is it readable? If it is readable it will be grammatically correct, the sentences will make sense, it will be free of internal inconsistencies, terms will be defined, it will contain appropriate graphics, and the like.
Second: Does it contain a complete set of all of the causal relationships? If it did contain a "complete set of all of the causal relationships" one could (at least): 1. Trace the causal relationships from the harmful outcomes to the deepest conditions, behaviors, actions, and inactions. 2. Show that the important attributes of the harmful outcomes were completely explained by the deepest conditions, behaviors, actions, and inactions.
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First Contact Resolution (FCR) Trends Report
Study the FCR by category to help give you insight to whether new knowledge articles could be useful on specific topics. This will also point you to agent training issues.
Ultimately, customers are more concerned with issue resolution than contact resolution—the call is just the means to the end, hopefully. Recognizing this, customer surveying should be geared to the type of issue that was reported. For instance, if it was a billing concern, it makes the most sense to contact the customer for resolution feedback after they have received the next bill rather than 2 days after they called the contact center. They may think their issue has been resolved but don't really know for sure until they see the correction on the next bill. An after-contact follow-up surveying approach that is geared to check back with the customer after a milestone has been accomplished probably makes the most sense for issues that take some time to resolve. Post-call surveys can easily be deployed to tackle one-and-done calls, to ensure that your agents are handling them effectively and to the satisfaction of callers.
A multi-source FCR measurement approach is best. Because it can be challenging and costly to measure first contact resolution, a multi-measure approach is more flexible. For instance, customer satisfaction surveys can be used to determine overall FCR performance, by contact type, while call quality monitoring results and post-call surveys can deliver agent-level FCR performance and at the same time, point out developmental improvement opportunities. Internal call statistics can be used to calculate overall center-level repeat-call performance, and if your system permits, agent and team level repeat-call performance. Try a set of measures to gather as much information as possible about your customer service response.
Once you have a good idea of your FCR performance, you can drill down to identify the call types that are not being resolved consistently in one contact. Then decide if it's even possible or desirable to resolve these types of calls or contacts in one call. If so, root cause analysis and process streamlining, automation, or more self-service options will boost your first call resolution performance, reduce repeat calls and rework, and ultimately reduce operating costs.
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IT Help Desk Metrics - First Contact Resolution Report
This is a trend customer service report showing the percentage of total service requests resolved by the Customer Service team over time. With this trend report, you are able to see your progress toward your goals.
Customer feedback surveys also have the potential to find out whether issues are ultimately resolved to the customers' satisfaction. Internal measurement can only assume, by the lack of a repeat contact, that the issue was resolved. You really don't know for sure if it was resolved or if the customer just gave up, unless you ask the customer. And the timing of when you do ask the customer is important too—has everything happened that needed to happen to resolve the problem?
Internal FCR metrics are necessary for root cause analysis and process streamlining. Call quality FCR determinations and FCR call stats are great for identifying training and coaching needs, and process improvement opportunities. Most CRM systems facilitate the tracking of customer contact. That is after all the goal of a customer relationship management system—to know everything possible about customers and their interaction with the company. Other customer support systems may not be structured to so easily track and measure contacts and resolution.
Agent logging can also gather FCR performance by contact type, however it's really not appropriate for measuring individual agent performance due to the built in bias of agents determining whether the contacts they handled were resolved or not. If you do use agent-driven measurement, audit the results periodically and/or use it in combination with other measures, such as a customer satisfaction measure of FCR and a call quality monitoring measure of FCR.
Repeat-call calculations, agent logging and tick sheets, and call quality-monitoring determinations are all approximations of customer experience. Most companies have found that internal first contact resolution measures are overstated—the customer's view of first contact resolution is usually lower than an internal measurement. In other words, don't get too comfortable with your measurement of your performance, ask your customers too. If you're primarily relying on internal measures, use customer feedback periodically to calibrate your performance.
Keep in mind that internal metrics are more prone to manipulation and may be more self-serving, depending upon how the data is collected, the scope, the qualifying window, repeat-call calculation definition, and subjectivity of the determination. Internal metrics are also subject to data integrity issues due to the difficulty of collecting and manually categorizing the data.
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First Contact Resolution (FCR) By Agent Report
How many of your customers' issues are resolved on the first contact? It sounds like it should be easy to measure, however many companies have found it difficult to define first contact resolution, much less measure it consistently. Tactics to measure first contact resolution vary greatly from company to company. Our survey confirms this. While some companies are measuring first contact resolution, many are not and would like to.
Customers expect to bring a problem or question to your attention and have it resolved in a timely manner. Not all inquiries can be resolved immediately or on the first contact. However, advances in technology, increasing employee empowerment, and scrutinizing evaluation will increase the number that can.
80% first contact resolution performance sounds good. Yet with an 80 percent first contact resolution, 20 percent of customers require multiple contacts with your company to achieve resolution. An 80 percent first contact resolution means your customers average 1.2 contacts to resolve a question or issue. The 20 percent repeat contacts represent increased call volume and field visits, inflated operating expenses, and most importantly, dissatisfied customers. Dissatisfied customers are more likely to defect and more likely to tell others about their experiences.
First Contact Resolution (FCR) is a critical determinant of customer satisfaction, making FCR one of the more powerful customer care metrics. Improvement in FCR brings the best of both worlds—improvement in efficiency and effectiveness. You don't have to worry that you are sacrificing quality because you are reducing costs, or vice versa. When you improve FCR you're improving quality, reducing costs, and improving customer satisfaction, all at the same time.
Measuring First Contact Resolution is the first step towards improvement. Due to the nature of what is being measured—an outcome—it can be challenging. Our research identified four primary measures—three of which are internal approximations of First Contact Resolution, the fourth provides true customer feedback and perception. While each approach has its application, customer perception is king—the customer's evaluation is what matters most.
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IT Service Performance Metrics Reports
This customer service report shows SLA compliance over a period of time. Managing trends toward a higher goal can dramatically increase customer satisfaction.
Service level agreements can contain numerous service performance metrics with corresponding service level objectives. A common case in IT service management is a call center or service desk. Metrics commonly agreed to in these cases include:
- ABA (Abandonment Rate): Percentage of calls abandoned while waiting to be answered.
- ASA (Average Speed to Answer): Average time (usually in seconds) it takes for a call to be answered by the service desk.
- TSF (Time Service Factor): Percentage of calls answered within a definite timeframe, e.g., 80% in 20 seconds.
- FCR (First-Call Resolution): Percentage of incoming calls that can be resolved without the use of a callback or without having the caller call back the helpdesk to finish resolving the case.
- TAT (Turn-Around Time): Time taken to complete a certain task.
Uptime is also a common metric, often used for data services such as shared hosting, virtual private servers and dedicated servers. Common agreements include percentage of network uptime, power uptime, number of scheduled maintenance windows, etc.
Many SLAs track to the Information Technology Infrastructure Library specifications when applied to IT services.
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Help Desk Service Level Agreement Detail Report By User
Drill down on the 239 tickets outside of the SLA.
Now review the detail to determine why these tickets are out of SLA. You can sort all headings to get see patterns and export to a PDF or CSV file and send to others as appropriate. Perhaps you can see if there is a common problems with a group of categories which is the "nature of request". On the right column, you can see the business days over/under SLA.
An important best practice is to never stop the SLA clock from ticking so that problems are not hidden. Giva has the ability to put a ticket on "hold" which is a type of designation whereby the amount of time the ticket was on "hold" is automatically calculated and booked into the ticket history as a note when the ticket is taken off "hold". So, if a tickets is out of SLA you can easily trace this back to a specific reason. Also, Administrators have the ability to back date the close of a ticket and a reason is required. There is also a report that shows tickets where the close was backdated.
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Average Close Time-Service Level Agreement Report
This is a great report to help you focus on the focus on the tickets that are out of SLA. You can see that Average Close Time in business hours and the percent within SLA.
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Respond and Resolve-Service Level Agreements
How will you prioritize the blizzard of requests from employees or customers? Do your best to prioritize requests based upon their impact to revenue generation.
Respond and resolve times will properly set expectations. See Giva whitepaper on SLAs:
https://www.givainc.com/wp/implementing-service-level-agreements-it-service-desk.cfm
This whitepaper teaches you how to prepare your customers for SLAs, how to write an SLA and how to get buy-in from customers/employees. An SLA is really an agreement between the support organization and your customers.
Respond and resolve times should be associated with each severity level.
Downtime from major outages or product failures, also need to measure the impact in terms of # of customers and quantify the # of hours of customers not productive. Giva Tsunami ticket report will show the number of hours and how many people affected.
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IT Help Desk Customer Satisfaction Trends Report
Good to look at raw data, but also need to see data in a trend line. See where you are going? What happened and why significant changes over time?
This report shows the results of the customer satisfaction surveys in the form of a trend report. This is very useful when used in conjunction with the SLA Compliance to demonstrate the level of service provided and the level of customer satisfaction your team is delivering to customers.
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IT Service Desk Customer Survey Metrics
This is another set of survey results. It is from a simple 1 question survey from the prior slide. Rate us and provide written feedback. Drilling down on the bottom is from Col 4. Clicking on the 480 shows more detail with a graphic.
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